%% Example of a LaTeX source file for a COLING-2012 submission
%% last updated: July 10, 2012
%% Optional instructions for authors within the tex file are provided as comments and start with 'for authors:...'
\documentclass[10pt,a5paper,twoside]{article}
\usepackage{coling2012}
\usepackage{amsmath}
\usepackage{latexsym}
\usepackage[draft]{fixme}
\usepackage{xspace}
\usepackage{relsize}
\usepackage{graphicx}
\usepackage[algoruled,vlined]{algorithm2e}
\usepackage{tikz}
\usetikzlibrary{automata}

\newcommand{\tup}[1]{\langle #1 \rangle}
\newcommand{\puse}{\ensuremath{\textsf{p}_\textit{use}}}
\newcommand{\randomuse}{\ensuremath{\textsf{rnd}_\emph{use}}\xspace}
\newcommand{\incuse}{\ensuremath{\textsf{inc}_\emph{use}}\xspace}
\newcommand{\RE}{\textsf{RE}\xspace}
\newcommand{\REL}{\textsf{REL}\xspace}
\newcommand{\IR}{\textrm{I}\!\textrm{R}}
\newcommand{\gM}{\mathcal{M}}
\newcommand{\el}{\ensuremath{\mathcal{EL}}\xspace}
\newcommand{\interp}[1]{|\!|#1|\!|}


\title{Probabilistic Refinement Algorithms\\for the Generation of Referring Expressions}
%for authors: in case of more than four author names ref. to commented line below 
%\author{$Annie~SMITH^{1, 2}~~~LI~Xiao Dong^{1, 3}$\\$~~~Third~Author^{1, 2}~~~Fourth~Author^{1, 3}~~~ Fifth~Author^{2, 3}$\\
\author{$Aaa~AAA^{1, 2}~~~Bbb~BBB^{1}~~~Ccc~CCC^{1}$\\
{\small  	(1) INSTITUTE\_1, address 1\\ 
 		(2) INSTITUTE\_2, address 2\\
  \texttt{aaa.aaa@mail.org, bbb.bbb@mail.org, ccc.ccc@mail.org} \\ 
}}

\begin{document}
\maketitle
%% The first mandatory ABSTRACT (\abstractEn) section below is for the English language
\abstractEn{In this paper we propose an algorithm for the generation of referring expressions that adapts the approach of~\cite{arec2:2008:Areces,arec:usin11} 
to include probabilities learned from corpora.  After introducing the algorithm we discuss how the probabilities required as 
imput can be computed for any given domain for which a suitable corpus of REs is available, and how the probabilities can be adjusted for new scenes in the domain using a machine learning approach.  We exemplify how to compute the 
probabilities over the GRE3D7 corpus of~\cite{viet:gene11}.\\
The resulting algorithm is able to generate different referring expressions for the same target with a frequency similar to that observed in corpora. Moreover, the most frequently generated referring expressions not in the corpus are also natural, indicating that the algorithm can generalize from the learning data. \\
We empirically evaluate the new algorithm over the GRE3D7 corpus, and show that the probability distribution of the generated referring expressions match the ones found in the corpus with high accuracy.}

%for authors: for keywords section either use \keywordsEn OR \keywordsOL below as relevant
%Example for English only keywords list
\keywordsEn{Generation of referring expressions, refinement algorithms, machine-learning}

%\newpage



%1. Generation of Referring Expresions
%2. Adding non-determisnism
%p_use es la probabilidad de usar la propiedad si elimina distractores. 
%3. Learning probabilities from corpus
%4. Adding overspecification
%5. Evaluation
%6. Discussion of Non Determinism and Overspecification
%7. Conclusions

\input{generating}
\input{addingprobabilities}
\input{learning}
\input{addingoverspecification}
\input{evaluation}
\input{discussion}
%\input{conclusions}

\bibliographystyle{apa}

\bibliography{coling2012}

\end{document}\begin{flushleft}\end{flushleft}
